Andrea Rosà

Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, 2022

Accurate Fork-Join Profiling on the Java Virtual Machine.

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[DOI]

Proceedings of the Euro-Par 2022: Parallel Processing, 2022

2021

Automated Large-scale Multi-language Dynamic Program Analysis in the Wild.

[BibT_eX]

[DOI]

Proceedings of the Software Engineering 2021, 2021

Automatically Assessing and Extending Code Coverage for NPM Packages.

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[DOI]

Proceedings of the 2nd IEEE/ACM International Conference on Automation of Software Test, 2021

2020

FJProf: Profiling Fork/Join Applications on the Java Virtual Machine.

[BibT_eX]

[DOI]

Eduardo Eduardo Rosales Rosero

Proceedings of the VALUETOOLS 2020: 13th EAI International Conference on Performance Evaluation Methodologies and Tools, 2020

Profiling streams on the Java virtual machine.

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[DOI]

Proceedings of the Programming'20: 4th International Conference on the Art, 2020

P<sup>3</sup>: A Profiler Suite for Parallel Applications on the Java Virtual Machine.

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[DOI]

Proceedings of the Programming Languages and Systems - 18th Asian Symposium, 2020

2019

Analysis and Optimization of Task Granularity on the Java Virtual Machine.

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[DOI]

ACM Trans. Program. Lang. Syst., 2019

Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild (Artifact).

[BibT_eX]

[DOI]

Dagstuhl Artifacts Ser., 2019

On Evaluating the Renaissance Benchmarking Suite: Variety, Performance, and Complexity.

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[DOI]

CoRR, 2019

NodeMOP: runtime verification for Node.js applications.

[BibT_eX]

[DOI]

Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing, 2019

Optimization coaching for fork/join applications on the Java virtual machine.

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[DOI]

Proceedings of the Conference Companion of the 3rd International Conference on Art, 2019

Renaissance: benchmarking suite for parallel applications on the JVM.

[BibT_eX]

[DOI]

Proceedings of the 40th ACM SIGPLAN Conference on Programming Language Design and Implementation, 2019

NAB: automated large-scale multi-language dynamic program analysis in public code repositories.

[BibT_eX]

[DOI]

Proceedings of the Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, 2019

Renaissance: a modern benchmark suite for parallel applications on the JVM.

[BibT_eX]

[DOI]

Proceedings of the Proceedings Companion of the 2019 ACM SIGPLAN International Conference on Systems, 2019

Automated Large-Scale Multi-Language Dynamic Program Analysis in the Wild (Tool Insights Paper).

[BibT_eX]

[DOI]

Proceedings of the 33rd European Conference on Object-Oriented Programming, 2019

2018

Optimizing type-specific instrumentation on the JVM with reflective supertype information.

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[DOI]

J. Vis. Lang. Comput., 2018

Understanding task granularity on the JVM: profiling, analysis, and optimization.

[BibT_eX]

[DOI]

Proceedings of the Conference Companion of the 2nd International Conference on Art, 2018

Analyzing and optimizing task granularity on the JVM.

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[DOI]

Proceedings of the 2018 International Symposium on Code Generation and Optimization, 2018

lpt: A Tool for Tuning the Level of Parallelism of Spark Applications.

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[DOI]

Proceedings of the 25th Asia-Pacific Software Engineering Conference, 2018

2017

Failure Analysis and Prediction for Big-Data Systems.

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[DOI]

IEEE Trans. Serv. Comput., 2017

ADRENALIN-RV: Android Runtime Verification Using Load-Time Weaving.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Software Testing, 2017

Speeding Up Type-Specific Instrumentation for the Analysis of Complex Systems.

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[DOI]

Proceedings of the 22nd International Conference on Engineering of Complex Computer Systems, 2017

Accurate reification of complete supertype information for dynamic analysis on the JVM.

[BibT_eX]

[DOI]

Proceedings of the 16th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, 2017

tgp: A Task-Granularity Profiler for the Java Virtual Machine.

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[DOI]

Proceedings of the 24th Asia-Pacific Software Engineering Conference, 2017

2016

AutoBench: Finding Workloads That You Need Using Pluggable Hybrid Analyses.

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[DOI]

Proceedings of the IEEE 23rd International Conference on Software Analysis, 2016

Extended Code Coverage for AspectJ-Based Runtime Verification Tools.

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[DOI]

Proceedings of the Runtime Verification - 16th International Conference, 2016

Adaptable Runtime Monitoring for the Java Virtual Machine.

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[DOI]

Proceedings of the Leveraging Applications of Formal Methods, Verification and Validation: Discussion, Dissemination, Applications, 2016

An Endpoint Communication Profiling Tool for Distributed Computing Frameworks.

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[DOI]

Proceedings of the 36th IEEE International Conference on Distributed Computing Systems, 2016

Actor profiling in virtual execution environments.

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[DOI]

Proceedings of the 2016 ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences, 2016

Profiling actor utilization and communication in Akka.

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[DOI]

Proceedings of the 15th International Workshop on Erlang, 2016

Efficient profiling of actor-based applications in parallel and distributed systems.

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[DOI]

Proceedings of the 11th Workshop on Implementation, 2016

AkkaProf: A Profiler for Akka Actors in Parallel and Distributed Applications.

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[DOI]

Proceedings of the Programming Languages and Systems - 14th Asian Symposium, 2016

2015

Demystifying Casualties of Evictions in Big Data Priority Scheduling.

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[DOI]

SIGMETRICS Perform. Evaluation Rev., 2015

Catching failures of failures at big-data clusters: A two-level neural network approach.

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[DOI]

Proceedings of the 23rd IEEE International Symposium on Quality of Service, 2015

Understanding the Dark Side of Big Data Clusters: An Analysis beyond Failures.

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[DOI]

Proceedings of the 45th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 2015

Understanding Unsuccessful Executions in Big-Data Systems.

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[DOI]

Proceedings of the 15th IEEE/ACM International Symposium on Cluster, 2015

Predicting and Mitigating Jobs Failures in Big Data Clusters.

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[DOI]